Map of Samples

# Abundance of Euphausia pacifica over Time

Most Detected Taxa

## # A tibble: 12 × 2
##    ID_Microscopy               n
##    <chr>                   <int>
##  1 Euphausia pacifica      21182
##  2 Nematoscelis difficilis 20967
##  3 Thysanoessa gregaria    12294
##  4 Nyctiphanes simplex     10117
##  5 Stylocheiron longicorne  7717
##  6 Euphausia recurva        6338
##  7 Euphausia gibboides      4430
##  8 Stylocheiron affine      4392
##  9 Thysanoessa spinifera    3579
## 10 Stylocheiron maximum     2567
## 11 Euphausia eximia         1311
## 12 Nematobrachion flexipes  1179
## Warning: There was 1 warning in `filter()`.
## ℹ In argument: `!is.na(year)`.
## Caused by warning in `is.na()`:
## ! is.na() applied to non-(list or vector) of type 'closure'

Abundance

Temperature

## Warning: The dot-dot notation (`..eq.label..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(eq.label)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Oxygen

## Warning: Removed 792 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 792 rows containing non-finite values (`stat_poly_eq()`).
## Removed 792 rows containing non-finite values (`stat_poly_eq()`).
## Warning: Removed 792 rows containing missing values (`geom_point()`).

## Warning: Removed 792 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 792 rows containing non-finite values (`stat_poly_eq()`).
## Warning: Removed 792 rows containing missing values (`geom_point()`).

# Abundance Temp + O2 Envelope

## Warning: Removed 134 rows containing missing values (`geom_point()`).

Detection Temp + O2 Envelope

## Warning: Removed 134 rows containing missing values (`geom_point()`).

## Warning: Removed 57 rows containing missing values (`geom_point()`).

# Site - Binomial vs. SST

Binomial | Station Run models

## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00455353 (tol = 0.002, component 1)
## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: binomial  ( logit )
## Formula: PA ~ (1 | ID_Microscopy) + mean_temp * mean_O2ml_L
##    Data: pa_adult_data
## 
##      AIC      BIC   logLik deviance df.resid 
##  18626.3  18666.5  -9308.2  18616.3    22711 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.2370 -0.5766 -0.2175 -0.0823 12.9409 
## 
## Random effects:
##  Groups        Name        Variance Std.Dev.
##  ID_Microscopy (Intercept) 3.147    1.774   
## Number of obs: 22716, groups:  ID_Microscopy, 12
## 
## Fixed effects:
##                        Estimate Std. Error z value Pr(>|z|)    
## (Intercept)           -11.19166    1.30134  -8.600  < 2e-16 ***
## mean_temp               0.82952    0.10671   7.774 7.63e-15 ***
## mean_O2ml_L             1.89486    0.25002   7.579 3.49e-14 ***
## mean_temp:mean_O2ml_L  -0.17096    0.02177  -7.851 4.12e-15 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) mn_tmp m_O2_L
## mean_temp   -0.912              
## mean_O2ml_L -0.902  0.959       
## mn_tm:_O2_L  0.908 -0.983 -0.990
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.00455353 (tol = 0.002, component 1)

Look at the models

Example Euphausia pacifica

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning in eval(family$initialize): non-integer #successes in a binomial glm!

## Warning: `fitted_draws` and `add_fitted_draws` are deprecated as their names were confusing.
## - Use [add_]epred_draws() to get the expectation of the posterior predictive.
## - Use [add_]linpred_draws() to get the distribution of the linear predictor.
## - For example, you used [add_]fitted_draws(..., scale = "response"), which
##   means you most likely want [add_]epred_draws(...).
## NOTE: When updating to the new functions, note that the `model` parameter is now
##   named `object` and the `n` parameter is now named `ndraws`.